Social network analysis is based on an assumption of the
importance of relationships among interacting units. The social network
perspective encompasses theories, models, and applications that are expressed in
terms of relational concepts or processes. Along with growing interest and
increased use of network analysis has come a consensus about the central
principles underlying the network perspective. In addition to the use of
relational concepts, we note the following as being important:

Actors
and their actions are viewed as interdependent rather than independent,
autonomous units

Relational
ties (linkages) between actors are channels for transfer or "flow" of
resources (either material or nonmaterial)

Network
models focusing on individuals view the network structural environment as
providing opportunities for or constraints on individual action

The unit of analysis in network analysis is not the
individual, but an entity consisting of a collection of individuals and the
linkages among them. Network methods focus on dyads (two actors and their ties),
triads (three actors and their ties), or larger systems (subgroups of
individuals, or entire networks.

Social network analysis has emerged as a set of methods for
the analysis of social structures, methods which are specifically geared towards
an investigation of the relational aspects of these structures. The use of these
methods, therefore, depends on the availability of relational rather than
attribute data.

Scott, J., 1992, Social Network Analysis. Newbury
Park CA: Sage.

Network analysis is the study of social relations among a
set of actors. It is a field of study -- a set of phenomena or data which we
seek to understand. In the process of working in this field, network researchers
have developed a set of distinctive theoretical perspectives as well. Some of
the hallmarks of these perspectives are:

focus
on relationships between actors rather than attributes of actors

sense
of interdependence: a molecular rather atomistic view

structure
affects substantive outcomes

emergent
effects

Network theory is sympathetic with systems theory and
complexity theory. Social networks is also characterized by a distinctive
methodology encompassing techniques for collecting data, statistical analysis,
visual representation, etc.

Social network analysis [SNA] is the mapping and measuring
of relationships and flows between people, groups, organizations, computers or
other information/knowledge processing entities. The nodes in the network are
the people and groups while the links show relationships or flows between the
nodes. SNA provides both a visual and a mathematical analysis of complex human
systems.

Network analysis (or social network analysis) is a set of
mathematical methods used in social psychology, sociology, ethology, and
anthropology. Network analysis assumes that the way the members of a group can
communicate to each other affect some important features of that group
(efficiency when performing a task, moral satisfaction, leadership). Network
analysis makes use of mathematical tools and concepts that belong to graph
theory. A network models a communication group. It consists of a number of nodes
(each node corresponding to a member of the group) and a number of edges (or
ties)¸each one being associated to a communication connection between two
actors. Network data is stored in an adjacency matrix. Commonly, the [i,j]
element of the adjacency matrix corresponds to the communication behavior of
actor ╬i' to actor ╬j'.

Social network analysis is
focused on uncovering the patterning of people's interaction. Network analysis
is based on the intuitive notion that these patterns are important features of
the lives of the individuals who display them. Network analysts believe that how
an individual lives depends in large part on how that individual is tied into
the larger web of social connections. Many believe, moreover, that the success
or failure of societies and organizations often depends on the patterning of
their internal structure. From the outset, the network approach to the study of
behavior has involved two commitments: (1) it is guided by formal theory
organized in mathematical terms, and (2) it is grounded in the systematic
analysis of empirical data. It was not until the 1970s, therefore--when modern
discrete combinatorics (particularly graph theory) experienced rapid development
and relatively powerful computers became readily available--that the study of
social networks really began to take off as an interdisciplinary specialty.
Since then its growth has been rapid. It has found important applications in
organizational behavior, inter-organizational relations, the spread of
contagious diseases, mental health, social support, the diffusion of information
and animal social organization.

Helps
collect and analyze structured qualitative and quantitative data including
freelists, pilesorts, triads, paired comparisons, and ratings. ANTHROPAC's
analytical tools include techniques that are unique to Anthropology, such as
consensus analysis, as well as standard multivariate tools such as multiple
regression, factor analysis, cluster analysis, multidimensional scaling and
correspondence analysis. In addition, the program provides a wide variety of
data manipulation and transformation tools, plus a full-featured matrix algebra
language.

A different kind of
network analysis program. FATCAT works with categorical who-to-whom matrices, in
which you select a variable that describes nodes to determine the categories for
rows (who) and another one to determine the categories for columns (whom).

One of the oldest
network analysis programs, NEGOPY finds cliques, liaisons, and isolates in
networks having up to 1,000 members and 20,000 links. In use at over 100
universities and research centers around the world.

StOCNET is an open
software system currently under development that will provide a new platform to
make a number of statistical methods that are presently privately owned
available to a wider audience. A new version that contains BLOCKS and SIENA can
be downloaded.

Software download
site for UCINET and Krackplot but also great and comprehensive introduction to
social network analysis through its Social Network Analysis Instructional Web
site that contains definitions, explanations, examples and slide shows: http://www.insna.org/indexConnect.html